The present invention relates generally to three-dimensional (3D) computerized tomography (CT) and more particularly to masking cone beam projection data generated from either a region of interest helical scan or a helical scan.
To acquire cone beam projection data in a cone-beam CT implementation, an object is scanned, preferably over a 360.degree. angular range, either by moving a cone beam x-ray source in a scanning circle about the object, while keeping a two-dimensional (2D) array detector fixed with reference to the cone beam x-ray source or by rotating the object while the x-ray source and detector remain stationary. The image of the object is reconstructed by using a Radon inversion process, in which the total Radon transform of the cone beam projection data is computed. The first step in the reconstruction process is to partition the cone beam projection data into a plurality of vertical planes in Radon space. Within each vertical plane, the Radon derivative data is computed. Next, the Radon derivative data is converted to Radon data on a plurality of polar grid points located on each vertical plane. A 3D inverse Radon transformation then converts the Radon data into an image. The image is then reconstructed for display.
A problem with the above-described Radon inversion process is that it is difficult to image an object having rather long, wide, or tall dimensions, because it is hard to procure a detector array having sufficient height or width to obtain the cone beam projection data. Generally, the detector array should have a height and width that is somewhat greater than the height and width of the object or region of interest of the object, otherwise, some x-ray data will be missed. If x-ray data is missed, then it will be very hard to image a region of interest of the object, since the cone beam projection data may not exclusively represent data from such a region of interest. Consequently, the height of the detector array limits the height of the region that can be scanned.
However, it is possible to scan and reconstruct an image of an object with cone beam x-rays, using a detector array that is shorter than the object. In this approach, the x-ray source scans the object along a helix scan path. In order to scan a region of interest of the object, a circular scan at the top level of the region of interest and a circular scan at the bottom level of the region of interest are added to the helical scan. The only height requirement is that the detector array should be longer than the distance between adjacent turns in the helical scan path. In order to reconstruct an image of the region of interest, it is necessary to compute the Radon transform for each plane intersecting the region of interest from the totality of the cone beam projection data. This is achieved by combining the cone beam projection data taken at different source positions on the scan path. Combining the cone beam projection data taken at different source positions on the scan path requires that the angular range of the cone beam projection data for each of the source positions be used to later compute the Radon derivative and that the exact number of source positions that contribute to a particular Radon point be maintained. The reconstruction process for this approach is very complicated and requires a lot of time and effort to perform.